acc {Rcpi} | R Documentation

## Auto Cross Covariance (ACC) for Generating Scales-Based Descriptors of the Same Length

### Description

Auto Cross Covariance (ACC) for Generating Scales-Based Descriptors of the Same Length

### Usage

    acc(mat, lag)

### Arguments

`mat` | A `p * n` matrix. Each row represents one scale (total `p` scales), each column represents one amino acid position (total `n` amino acids).
`lag` | The lag parameter. Must be less than the amino acids.

### Details

This function calculates the auto covariance and auto cross covariance for generating scale-based descriptors of the same length.

### Value

A length `lag * p^2` named vector, the element names are constructed by: the scales index (crossed scales index) and lag index.

### Note

To know more details about auto cross covariance, see the references.

### Author(s)

Nan Xiao <https://nanx.me>

### References

Wold, S., Jonsson, J., Sj\"orstr\"om, M., Sandberg, M., & R\"annar, S. (1993). DNA and peptide sequences and chemical processes multivariately modelled by principal component analysis and partial least-squares projections to latent structures. Analytica chimica acta, 277(2), 239–253.

Sj\"ostr\"om, M., R\"annar, S., & Wieslander, A. (1995). Polypeptide sequence property relationships in Escherichia coli based on auto cross covariances. Chemometrics and intelligent laboratory systems, 29(2), 295–305.

### See Also

See `extractPCMScales` for generalized scales-based descriptors. For more details, see `extractPCMDescScales` and `extractPCMPropScales`.

### Examples

    p = 8    # p is the scales number
    n = 200  # n is the amino acid number
    lag = 7  # the lag paramter
    mat = matrix(rnorm(p * n), nrow = p, ncol = n)
    acc(mat, lag)

[Package Rcpi version 1.26.0 Index]